公开记录
软件健康报告模式 0.27.0 · 指标 1.13.0 · 2026-07-26 07:41 UTC

debbiemarkslab / EVcouplings

Evolutionary couplings from protein and RNA sequence alignments

Jupyter Notebook · Python自定义许可证★ 313 星标⑂ 83 复刻始于 2016年7月在 GitHub 上查看 ↗
#structure-prediction#3d-structure#protein#protein-complexes

debbiemarkslab/EVcouplings 的健康指数为 100 分中的 54 分，处于「中等」区间。 其得分最高的类别是Engineering Quality（72/100），最低的是Vitality（31/100）。 最近一次更新在 96 天前。 近期的大部分工作由 1 位贡献者完成。

54
总分 / 100
中等

软件健康指数

指标归入加权类别，统一采用 1–100 量表。总体分先取类别加权平均；当公开证据触发高风险司法辖区政策时，评级会按政策调整，并设置 49（有风险）的上限。AI 就绪度不计入总体分。

54
优秀85-100堪称典范；基本满足所有检验标准
良好70-84健康；仅有轻微不足
中等50-69可接受，但存在明显不足；建议进行审查
存在风险30-49存在重大薄弱环节；采用时应保持审慎
危急1-29问题严重（项目被弃置、仅有单一维护者、缺乏基本工程规范）
活力社区与采用可持续性与治理工程质量安全AI 就绪度

评分画像

每条轴代表一个类别。形状比平均值更重要——健康的对象会填满整个图形，而“一峰一谷”式画像意味着某一维度的优势正掩盖另一维度的风险。

所有权

Debora Marks Lab组织
135 关注者33 个公开仓库始于 2014年9月

该仓库由组织支持——共同承担、可问责的托管责任，可延续于任何单一维护者之后。

软件包生态系统

注册表软件包版本月下载量版本数最近发布标签
PyPIevcouplings0.2.1-7627 天前analysiscouplingsevolutionary

按类别列示的指标

活力

项目是否仍有生命——是否仍在编写代码，是否仍在发布版本？

31存在风险 · 占总体的 22%

开发活跃度

22危急
评分方式
9.9/36推送新近度 — 最近一次推送于 96 天前
2.1/36提交节奏 — 52 周中有 3 周有提交
9.7/18提交量 — 最近一年 11 次提交
0/10OpenSSF Scorecard：Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
所用输入
commits_last_year11
human_commit_share1
days_since_last_push96
active_weeks_last_year3

发布纪律

44存在风险
评分方式
27/27有发布版本 — 已发布 7 个发布版本
7.2/36发布时效 — 最近一次发布版本于 627 天前
5.4/27发布节奏 — 约每 436.7 天发布一次
0/10OpenSSF Scorecard：Signed-Releases — 无数据
所用输入
releases_count7
latest_release_tagv0.2.1
releases_from_tags否
days_since_latest_release627
mean_days_between_releases436.7
已排除计分（无数据或不适用）：OpenSSF Scorecard：Signed-Releases。 其余权重已重新归一化。

社区与采用

项目是否拥有用户、下载量与关注度，并具备欢迎贡献者参与的配置？

55中等 · 占总体的 18%

流行度与采用

64中等
评分方式
40.5/60星标 — 313 个星标
16/25复刻 — 83 个复刻
7.7/15关注者 — 25 位关注者
所用输入
forks83
stars313
watchers25
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

社区健康

44存在风险
评分方式
22.5/22.5README
16.9/22.5许可证 — 存在许可证文件，但不是可识别的许可证
0/18CONTRIBUTING 指南
0/13.5行为准则
0/7.2议题模板
0/6.3PR 模板
所用输入
has_readme是
has_license是
has_contributing否
has_issue_template否
has_code_of_conduct否
has_pull_request_template否

可持续性与治理

项目能否在其成员之外延续——巴士系数、响应能力、由谁支持，以及软件包的维护状况？

61中等 · 占总体的 24%

维护者韧性（巴士系数）

39存在风险
评分方式
9/54巴士系数 — 1 位贡献者贡献了半数提交
8.2/22.5提交分布 — 头号贡献者编写了 63% 的提交
12.2/13.5贡献者广度 — 9 位贡献者
10/10OpenSSF Scorecard：Contributors — project has 10 contributing companies or organizations
所用输入
bus_factor1
contributors_sampled9
top_contributor_share0.634

议题与 PR 响应能力

66中等
评分方式
32.9/46.8议题解决 — 70% 的议题已关闭
31.3/38.3PR 接受 — 已裁定的 PR 中 108/132 已合并
1.5/15OpenSSF Scorecard：Code-Review — Found 1/6 approved changesets -- score normalized to 1
所用输入
merged_prs108
open_issues59
closed_issues140
issue_closed_ratio0.704
closed_unmerged_prs24

所有权与托管责任

68中等
评分方式
30/30所有权背书 — 组织持有
0/20已验证域名
15.3/25所有者影响力 — debbiemarkslab 有 135 位关注者
23.2/25既往记录 — 33 个公开仓库，账户约 11 年
所用输入
followers135
owner_typeOrganization
is_verified—
owner_logindebbiemarkslab
public_repos33
account_age_days4,316

软件包维护

79良好
评分方式
25/25已发布且可解析 — pypi 上有 1 个软件包
14/35发布时效 — 最近一次发布于 627 天前
20/20版本历史 — 7 个已发布版本
20/20未被弃用 — 活跃，未被弃用或撤回
所用输入
packagesevcouplings
ecosystemspypi
any_deprecated否
min_days_since_publish627

工程质量

基础的工程与文档实践是否到位？

72良好 · 占总体的 20%

工程实践

54中等
评分方式
24/24CI 工作流 — 2 个工作流
24/24存在测试
0/16Linter 配置
0/9.6Pre-commit 钩子
0/6.4.editorconfig
6/20OpenSSF Scorecard：CI-Tests — 2 out of 6 merged PRs checked by a CI test -- score normalized to 3
所用输入
has_ci是
has_tests是
has_editorconfig否
has_linter_config否
has_precommit_config否

文档

100优秀
评分方式
30/30README
25/25文档目录
15/15文档 / 主页站点 — http://evcouplings.org
10/10仓库描述
10/10主题标签 — 4 个主题标签
10/10Wiki
所用输入
topicsstructure-prediction, 3d-structure, protein, protein-complexes
has_wiki是
homepagehttp://evcouplings.org
has_readme是
has_docs_dir是
has_description是

安全

可见的安全与供应链实践是否稳固，且不存在未解决的高风险司法辖区暴露？

50中等 · 占总体的 16%

安全态势

37存在风险
评分方式
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — 无数据
0.8/2.5CI-Tests — 2 out of 6 merged PRs checked by a CI test -- score normalized to 3
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-Review — Found 1/6 approved changesets -- score normalized to 1
2.5/2.5Contributors — project has 10 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5许可证 — license file detected
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packaging — 无数据
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — 无数据
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
所用输入
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate3.7
已排除计分（无数据或不适用）：branch_protection, packaging, signed_releases。 其余权重已重新归一化。

依赖安全公告

100优秀
评分方式
35/35直接依赖不含已知公告 — 没有直接依赖携带已知公告
25/25间接依赖不含已知公告 — 没有间接依赖携带已知公告
0/40没有长期未处理的公告 — 没有公告带有发布日期
所用输入
sourceosv
advisories0
affected_packages0
assessed_packages39
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
已排除计分（无数据或不适用）：没有长期未处理的公告。 其余权重已重新归一化。 比对的是 pypi:evcouplings@0.2.1 的运行时依赖闭包——安装已发布的软件包时真正被拉取进来的内容——共 39 个软件包。 未对可达性进行分析。

AI 就绪度

该仓库在多大程度上具备与 AI 编码代理协同开发与维护的条件？这是一枚独立的实验性徽章——权重为 0.0，因此单独呈现，不影响总体健康评分。

34存在风险 · 占总体的 0%

AI 代理上下文与指引

13危急
评分方式
0/45代理指令 — 没有 CLAUDE.md / AGENTS.md / 编辑器规则
0/15机器可读文档（llms.txt）
13.3/40可读的提交历史 — 100 次人类提交中有 25 次说明了意图（结构化标题或解释性正文）
所用输入
has_llms_txt否
legible_history_share0.25
agent_instruction_files—
agent_instruction_max_bytes—

验证循环（构建 / 测试 / 类型检查）

40存在风险
评分方式
18/18一条命令的引导启动 — docs/Makefile
22/22自动化测试
0/11Lint / 格式化配置
0/11静态类型检查
0/10可复现环境
0/10已体现的代理实践 — 最近 100 次提交中没有代理编写的提交
0/8自动化维护 — 未观察到自动依赖更新
0/10OpenSSF Scorecard：Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
所用输入
has_nix否
has_tests是
lockfiles—
has_dockerfile否
typed_language否
bootstrap_filesdocs/Makefile
has_devcontainer否
has_linter_config否
typecheck_configs—
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

面向模型的代码可读性

54中等
评分方式
0/45可类型检查的代码 — Jupyter Notebook，未配置类型检查
53.6/55可控的文件大小 — 采样的 81 个源文件中有 2 个超过 60KB
所用输入
primary_languageJupyter Notebook
largest_source_bytes263,767
source_files_sampled81
oversized_source_files2

机器可读接口

40存在风险
评分方式
0/40API 模式（OpenAPI/GraphQL/proto）
0/20MCP 服务器
40/40可运行示例 — example, notebooks
所用输入
example_dirsexample, notebooks
has_mcp_signal否
api_schema_files—

关键数据

313GitHub 星标
9贡献者
11最近 12 个月提交数
96距最近推送天数
7发布版本数
1巴士系数（bus factor）
59开放议题
PyPI软件包生态系统数

数据采集警告

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

更多细节

Star 与 Fork 历史 0 ★ / 83 ⇿
0Star
83Fork
6发布

每颗 star 和每个 fork 的添加时间，来自 GitHub 并按天汇总。累计增长位于其构成来源——每日新增——的正上方，二者可相互对照：稳定的自然增长与短暂的突增形态截然不同。当这一差别可被衡量时，它会作为增长真实性予以报告。

0204060807732017-092022-022026-07
主版本 0次版本 0修订 6

每个点涵盖 9 天。

OpenSSF Scorecard 3.7 / 10
3.7综合

来自开源项目 OpenSSF Scorecard 的独立、工具无关的安全评估。每项检查奖励的是安全实践本身，而非特定供应商的工具。Scorecard 无法判定的检查项标记为 不适用，并从安全评分中剔除（绝不按零分计）。Scorecard v5.5.0 · 2026-07-26 07:41 UTC

10Binary-Artifactsno binaries found in the repo
不适用Branch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
3CI-Tests2 out of 6 merged PRs checked by a CI test -- score normalized to 3
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 1/6 approved changesets -- score normalized to 1
10Contributorsproject has 10 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
不适用Packagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
不适用Signed-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
直接依赖 18
注册表软件包版本约束清单文件
PyPIbilliard—pyproject.toml
PyPIbiopython>=1.84pyproject.toml
PyPIbokeh—pyproject.toml
PyPIclick—pyproject.toml
PyPIfilelock—pyproject.toml
PyPIjinja2—pyproject.toml
PyPImatplotlib—pyproject.toml
PyPImsgpack—pyproject.toml
PyPInumba—pyproject.toml
PyPInumpy—pyproject.toml
PyPIpandas—pyproject.toml
PyPIpsutil—pyproject.toml
PyPIrequests—pyproject.toml
PyPIruamel.yaml<0.18pyproject.toml
PyPIscikit-learn—pyproject.toml
PyPIscipy—pyproject.toml
PyPIseaborn—pyproject.toml
PyPIsetuptools>=18.2pyproject.toml
全部依赖 18

来自 GitHub 依赖图的完整解析依赖集合：18 个直接依赖与 0 个间接（传递）软件包。仓库提交锁文件时，传递闭包才是完整的。

注册表软件包版本关系
PyPIbilliard—直接
PyPIbiopython—直接
PyPIbokeh—直接
PyPIclick—直接
PyPIfilelock—直接
PyPIjinja2—直接
PyPImatplotlib—直接
PyPImsgpack—直接
PyPInumba—直接
PyPInumpy—直接
PyPIpandas—直接
PyPIpsutil—直接
PyPIrequests—直接
PyPIruamel-yaml—直接
PyPIscikit-learn—直接
PyPIscipy—直接
PyPIseaborn—直接
PyPIsetuptools—直接
依赖安全公告 0

安装 pypi:evcouplings@0.2.1 会引入 39 个包（直接与传递）：其中 0 个存在已知公告，0 个为直接依赖。

没有已知公告影响已评估的依赖。

公告表示依赖图中记录的版本落入某条公告的受影响范围。可达性未经分析，且依赖图包含开发与测试的版本固定——某项发现可能只涉及工具链而非交付的软件。

原始 JSON 报告 机器可读
{
  "data": {
    "repo": {
      "topics": [
        "structure-prediction",
        "3d-structure",
        "protein",
        "protein-complexes"
      ],
      "is_fork": false,
      "size_kb": 19375,
      "has_wiki": true,
      "homepage": "http://evcouplings.org",
      "languages": {
        "Python": 973487,
        "Jupyter Notebook": 1112585
      },
      "pushed_at": "2026-04-20T13:02:50Z",
      "created_at": "2016-07-20T18:15:45Z",
      "owner_type": "Organization",
      "updated_at": "2026-07-22T16:01:41Z",
      "description": "Evolutionary couplings from protein and RNA sequence alignments",
      "is_archived": false,
      "is_disabled": false,
      "license_spdx": null,
      "default_branch": "develop",
      "license_spdx_raw": "NOASSERTION",
      "primary_language": "Jupyter Notebook",
      "significant_languages": [
        "Jupyter Notebook",
        "Python"
      ]
    },
    "owner": {
      "blog": "https://marks.hms.harvard.edu/",
      "name": "Debora Marks Lab",
      "type": "Organization",
      "login": "debbiemarkslab",
      "company": null,
      "location": "Boston, MA",
      "followers": 135,
      "avatar_url": "https://avatars.githubusercontent.com/u/8976419?v=4",
      "created_at": "2014-09-30T19:46:58Z",
      "is_verified": null,
      "public_repos": 33,
      "account_age_days": 4316
    },
    "license": {
      "state": "custom",
      "spdx_id": null,
      "raw_spdx": "NOASSERTION",
      "file_present": true,
      "scorecard_found": true,
      "profile_has_license": true
    },
    "activity": {
      "releases": [
        {
          "tag": "v0.2.1",
          "kind": "patch",
          "published_at": "2024-11-05T11:16:06Z"
        },
        {
          "tag": "v0.1.1",
          "kind": "patch",
          "published_at": "2020-11-06T16:59:48Z"
        },
        {
          "tag": "v0.0.5",
          "kind": "patch",
          "published_at": "2018-09-16T14:17:14Z"
        },
        {
          "tag": "v0.0.4",
          "kind": "patch",
          "published_at": "2018-06-10T16:58:00Z"
        },
        {
          "tag": "v0.0.3",
          "kind": "patch",
          "published_at": "2018-04-05T16:56:55Z"
        },
        {
          "tag": "v0.0.2",
          "kind": "patch",
          "published_at": "2018-02-22T22:29:55Z"
        },
        {
          "tag": "v0.0.1",
          "kind": "patch",
          "published_at": "2017-09-03T13:29:15Z"
        }
      ],
      "recent_commits": [
        {
          "oid": "14c83457c6cfca8156aabe0615067447a2169791",
          "body": "fixed a3m import/sequence parsing",
          "is_bot": false,
          "headline": "Merge pull request #336 from debbiemarkslab/file_imports",
          "author_name": "thomashopf",
          "author_login": "thomashopf",
          "committed_at": "2026-04-20T13:02:44Z",
          "body_truncated": false,
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        },
        {
          "oid": "819547b9c9f2514f58539ba905fffebc6b44d326",
          "body": null,
          "is_bot": false,
          "headline": "fixed a3m import/sequence parsing",
          "author_name": "Ethan Eschbach-ete456",
          "author_login": null,
          "committed_at": "2026-04-20T12:48:42Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "522b0d185411fab8e166ba4d8abc38a3e0556880",
          "body": "only lowercase columns if at least one column affected, fixes #327",
          "is_bot": false,
          "headline": "Merge pull request #332 from debbiemarkslab/filtering-bug",
          "author_name": "thomashopf",
          "author_login": "thomashopf",
          "committed_at": "2025-10-23T14:59:25Z",
          "body_truncated": false,
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        },
        {
          "oid": "e550a6a347df9169a0f6f72c83118b7d6bed1d8a",
          "body": null,
          "is_bot": false,
          "headline": "only lowercase columns if at least one column affected, fixes #327",
          "author_name": "Thomas Hopf",
          "author_login": "thomashopf",
          "committed_at": "2025-10-23T14:54:30Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "92c5d6faa94630f54e2fad11844c7fd68ff0fd46",
          "body": "Fix regressions related to structure loading",
          "is_bot": false,
          "headline": "Merge pull request #331 from debbiemarkslab/pdb-loading-fixes",
          "author_name": "thomashopf",
          "author_login": "thomashopf",
          "committed_at": "2025-10-23T10:27:20Z",
          "body_truncated": false,
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        {
          "oid": "f80222a5593212fa3915c66c2efdd7cedd9cb3ad",
          "body": null,
          "is_bot": false,
          "headline": "fix residue 3 to 1 mapping to cover nonstandard AAs too",
          "author_name": "Thomas Hopf",
          "author_login": "thomashopf",
          "committed_at": "2025-10-22T11:05:30Z",
          "body_truncated": false,
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                "max_points": 2.5
              },
              {
                "key": "dangerous_workflow",
                "name": "Dangerous-Workflow",
                "detail": "no dangerous workflow patterns detected",
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "dependency_update_tool",
                "name": "Dependency-Update-Tool",
                "detail": "no update tool detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "fuzzing",
                "name": "Fuzzing",
                "detail": "project is not fuzzed",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "license",
                "name": "License",
                "detail": "license file detected",
                "points": 2.2,
                "status": "partial",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "packaging",
                "name": "Packaging",
                "detail": "packaging workflow not detected",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool is not run on all commits -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file not detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "no releases found",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "0 existing vulnerabilities detected",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "key": "dependency_advisories",
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            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
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                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
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                "code": "advisories_scope_published",
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                  "assessed": 39
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              },
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              "unassessed_packages": 0,
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              "direct_affected_packages": 0
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            "note": null,
            "notes": [],
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            "inputs": {
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              "meaning": "reported as a malicious package by the OpenSSF corpus; the remedy is removal or moving off the compromised name, never an upgrade of the same artifact. Versions the registry has since pulled are listed but not scored",
              "packages": [],
              "red_flag": false,
              "assessed_packages": 39,
              "malicious_packages": 0,
              "direct_malicious_packages": 0,
              "withdrawn_malicious_packages": 0,
              "installable_malicious_packages": 0
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            "components": [
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                "details": [
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          {
            "key": "high_risk_jurisdiction_exposure",
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            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
                "params": {}
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            "value": 100,
            "inputs": {
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              "red_flag": false,
              "exposures": [],
              "policy_countries": [
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                "Iran",
                "North Korea"
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              "review_only_matches": 0,
              "assessed_self_published_locations": 11
            },
            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
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                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "jurisdiction_no_match",
                    "params": {}
                  }
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                "max_points": 100
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          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "at_risk",
        "name": "AI Readiness",
        "value": 34,
        "weight": 0,
        "metrics": [
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            "key": "ai_agent_context",
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            "name": "Agent context & guidance",
            "note": null,
            "notes": [],
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            "inputs": {
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              "legible_history_share": 0.25,
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            "components": [
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                "key": "agent_instructions",
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                "detail": "no CLAUDE.md / AGENTS.md / editor rules",
                "points": 0,
                "status": "missed",
                "details": [
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                    "code": "no_agent_instructions",
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                "max_points": 45
              },
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                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
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                "key": "legible_commit_history",
                "name": "Legible commit history",
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                "points": 13.3,
                "status": "partial",
                "details": [
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                    "code": "legible_history",
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                      "sampled": 100
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                "max_points": 40
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              "lockfiles": [],
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              "has_devcontainer": false,
              "has_linter_config": false,
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              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
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            "components": [
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                "key": "one_command_bootstrap",
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                "points": 18,
                "status": "met",
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                "max_points": 18
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              {
                "key": "automated_tests",
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                "detail": null,
                "points": 22,
                "status": "met",
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              {
                "key": "lint_format_config",
                "name": "Lint / format config",
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                "points": 0,
                "status": "missed",
                "details": [],
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              },
              {
                "key": "static_type_checking",
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                "points": 0,
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                "max_points": 11
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                "key": "automated_maintenance",
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                "points": 0,
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                "details": [
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                    "code": "no_dependency_automation",
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                "max_points": 8
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                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
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            "key": "ai_code_legibility",
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              "largest_source_bytes": 263767,
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              "oversized_source_files": 2
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                "max_points": 45
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                "key": "manageable_file_sizes",
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                "points": 53.6,
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        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
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  "warnings": [
    "Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token"
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  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/d/debbiemarkslab/EVcouplings.svg",
  "full_name": "debbiemarkslab/EVcouplings",
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}

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评分是信号，而非担保。 评分反映的是 GitHub 上公开可见的实践——不是代码审计，也不是安全保证。

缺失数据将被剔除并重新归一化权重，绝不按零分计。方法论已版本化并公开：指标 v1.13.0、模式 v0.27.0—— 完整方法论 · 指标知识库.

单项结果在整体记录中的位置： 汇总统计 — PyPI.